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Re: st: margin vs mfx
Fernando Rios Avila <email@example.com>
Re: st: margin vs mfx
Fri, 23 Sep 2011 21:33:13 -0400
Thank you very much Tirthankar!
I didnt know that particularity of margins. and will help me correct
On Fri, Sep 23, 2011 at 9:28 PM, Tirthankar Chakravarty
> -margins- wants you to explicitly declare factor variables as such
> during estimation, else they are considered as continuous, whereas
> -mfx- and -dprobit- gauge this from the possible values:
> sysuse auto, clear
> generate goodplus = rep78 >= 4 if rep78 < .
> dprobit foreign mpg goodplus
> probit foreign mpg goodplus
> probit foreign mpg i.goodplus
> margins, dydx(*) atmeans
> On Fri, Sep 23, 2011 at 11:52 AM, Fernando Rios Avila
> <firstname.lastname@example.org> wrote:
>> Dear Stata listers,
>> I was checking some of my old program files which im trying to update,
>> and found one issue I hope someone can help me with.
>> The problem is that When I run the old program -dprobit- the marginal
>> results reported there are identical to the ones obtain using -mfx-
>> after a probit model.
>> However, when I apply the margin command, i cant obtain the same
>> results. they are similar, but not the same.
>> for instance see the following results:
>> Here is an example of the differences im finding:
>> sysuse auto
>> help dprobit
>> generate goodplus = rep78 >= 4 if rep78 < .
>> dprobit foreign mpg goodplus
>> Probit regression, reporting marginal effects Number of obs = 69
>> LR chi2(2) = 30.92
>> Prob > chi2 = 0.0000
>> Log likelihood = -26.942114 Pseudo R2 = 0.3646
>> foreign dF/dx Std. Err. z P>z x-bar [
>> 95% C.I. ]
>> mpg .0249187 .0110853 2.30 0.022 21.2899 .003192 .046646
>> goodplus* .4740077 .1114816 3.81 0.000 .42029 .255508 .692508
>> obs. P .3043478
>> pred. P .2286624 (at x-bar)
>> (*) dF/dx is for discrete change of dummy variable from 0 to 1
>> z and P>z correspond to the test of the underlying coefficient being 0
>> probit foreign mpg goodplus
>> Marginal effects after probit
>> y = Pr(foreign) (predict)
>> = .22866238
>> variable dy/dx Std. Err. z P>z [ 95% C.I. ] X
>> mpg .0249187 .01109 2.25 0.025 .003192 .046646 21.2899
>> goodplus* .4740077 .11148 4.25 0.000 .255508 .692508 .42029
>> (*) dy/dx is for discrete change of dummy variable from 0 to 1
>> margins, dydx(*) atmeans
>> Conditional marginal effects Number of obs = 69
>> Model VCE : OIM
>> Expression : Pr(foreign), predict()
>> dy/dx w.r.t. : mpg goodplus
>> at : mpg = 21.28986 (mean)
>> goodplus = .4202899 (mean)
>> dy/dx Std. Err. z P>z [95% Conf. Interval]
>> mpg .0249187 .0110854 2.25 0.025 .0031918 .0466455
>> goodplus .46276 .1187437 3.90 0.000 .2300267 .6954933
>> Is there anyway to obtain the same results?
>> I know this must be an old issue, but cant seem to find references to this.
>> Thanks in advance.
>> * For searches and help try:
>> * http://www.stata.com/help.cgi?search
>> * http://www.stata.com/support/statalist/faq
>> * http://www.ats.ucla.edu/stat/stata/
> Tirthankar Chakravarty
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
* For searches and help try: